Keynote Speakers

Mérouane Debbah, Mohamed Bin Zayed University of Artificial Intelligence, UAE

Date/Time: Tuesday May 31, 2022 - 9:00 am

Keynote Tile: Building the theoretical foundations of 6G

Abstract: Coming Soon

Mérouane Debbah is Chief Researcher at the Technology Innovation Institute in Abu Dhabi. He is an Adjunct Professor with the Department of Machine Learning at the Mohamed Bin Zayed University of Artificial Intelligence. He received the M.Sc. and Ph.D. degrees from the Ecole Normale Supérieure Paris-Saclay, France. He was with Motorola Labs, Saclay, France, from 1999 to 2002, and also with the Vienna Research Center for Telecommunications, Vienna, Austria, until 2003. From 2003 to 2007, he was an Assistant Professor with the Mobile Communications Department, Institut Eurecom, Sophia Antipolis, France. In 2007, he was appointed Full Professor at CentraleSupelec, Gif-sur-Yvette, France. From 2007 to 2014, he was the Director of the Alcatel-Lucent Chair on Flexible Radio. From 2014 to 2021, he was Vice-President of the Huawei France Research Center. He was jointly the director of the Mathematical and Algorithmic Sciences Lab as well as the director of the Lagrange Mathematical and Computing Research Center. Since 2021, he is leading the AI & Telecom Systems center at the Technology Innovation Institute. He has managed 8 EU projects and more than 24 national and international projects. His research interests lie in fundamental mathematics, algorithms, statistics, information, and communication sciences research. He is an IEEE Fellow, a WWRF Fellow, a Eurasip Fellow, an AAIA Fellow, an Institut Louis Bachelier Fellow and a Membre émérite SEE. He was a recipient of the ERC Grant MORE (Advanced Mathematical Tools for Complex Network Engineering) from 2012 to 2017. He was a recipient of the Mario Boella Award in 2005, the IEEE Glavieux Prize Award in 2011, the Qualcomm Innovation Prize Award in 2012, the 2019 IEEE Radio Communications Committee Technical Recognition Award and the 2020 SEE Blondel Medal. He received more than 20 best paper awards, among which the 2007 IEEE GLOBECOM Best Paper Award, the Wi-Opt 2009 Best Paper Award, the 2010 Newcom++ Best Paper Award, the WUN CogCom Best Paper 2012 and 2013 Award, the 2014 WCNC Best Paper Award, the 2015 ICC Best Paper Award, the 2015 IEEE Communications Society Leonard G. Abraham Prize, the 2015 IEEE Communications Society Fred W. Ellersick Prize, the 2016 IEEE Communications Society Best Tutorial Paper Award, the 2016 European Wireless Best Paper Award, the 2017 Eurasip Best Paper Award, the 2018 IEEE Marconi Prize Paper Award, the 2019 IEEE Communications Society Young Author Best Paper Award, the 2021 Eurasip Best Paper Award, the 2021 IEEE Marconi Prize Paper Award as well as the Valuetools 2007, Valuetools 2008, CrownCom 2009, Valuetools 2012, SAM 2014, and 2017 IEEE Sweden VT-COM-IT Joint Chapter best student paper awards. He is an Associate Editor-in-Chief of the journal Random Matrix: Theory and Applications. He was an Associate Area Editor and Senior Area Editor of the IEEE TRANSACTIONS ON SIGNAL PROCESSING from 2011 to 2013 and from 2013 to 2014, respectively. From 2021 to 2022, he serves as an IEEE Signal Processing Society Distinguished Industry Speaker

Zhu Han, ECE Department & CS Department, University of Houston, USA

Date/Time: Wednesday June 1, 2022 - 9:00 am

Keynote Title: Federated Learning and Analysis with Multi-access Edge Computing

Abstract In recent years, mobile devices are equipped with increasingly advanced computing capabilities, which opens up countless possibilities for meaningful applications. Traditional cloud-based Machine Learning (ML) approaches require the data to be centralized in a cloud server or data center. However, this results in critical issues related to unacceptable latency and communication inefficiency. To this end, multi-access edge computing (MEC) has been proposed to bring intelligence closer to the edge, where data is originally generated. However, conventional edge ML technologies still require personal data to be shared with edge servers. Recently, in light of increasing privacy concerns, the concept of Federated Learning (FL) has been introduced. In FL, end devices use their local data to train a local ML model required by the server. The end devices then send the local model updates instead of raw data to the server for aggregation. FL can serve as enabling technology in MEC since it enables the collaborative training of an ML model and also enables ML for mobile edge network optimization. However, in a large-scale and complex mobile edge network, FL still faces implementation challenges with regard to communication costs and resource allocation. In this talk, we begin with an introduction to the background and fundamentals of FL. Then, we discuss several potential challenges for FL implementation. In addition, we study the extension to Federated Analysis (FA) with potential applications.

Zhu Han received the B.S. degree in electronic engineering from Tsinghua University, in 1997, and the M.S. and Ph.D. degrees in electrical engineering from the University of Maryland, College Park, in 1999 and 2003, respectively. From 2000 to 2002, he was an R&D Engineer of JDSU, Germantown, Maryland. From 2003 to 2006, he was a Research Associate at the University of Maryland. From 2006 to 2008, he was an assistant professor in Boise State University, Idaho. Currently, he is a John and Rebecca Moores Professor in Electrical and Computer Engineering Department as well as Computer Science Department at University of Houston, Texas. His research interests include security, wireless resource allocation and management, wireless communication and networking, game theory, and wireless multimedia. Dr. Han is an NSF CAREER award recipient of 2010. Dr. Han has several IEEE conference best paper awards, and winner of 2011 IEEE Fred W. Ellersick Prize, 2015 EURASIP Best Paper Award for the Journal on Advances in Signal Processing and 2016 IEEE Leonard G. Abraham Prize in the field of Communication Systems (Best Paper Award for IEEE Journal on Selected Areas on Communications). Dr. Han is the winner 2021 IEEE Kiyo Tomiyasu Award. He has been an IEEE fellow since 2014, AAAS fellow since 2020 and IEEE Distinguished Lecturer from 2015 to 2018. Dr. Han is a 1% highly cited researcher according to Web of Science since 2017.

Magdy Bayoumi, Department Head, Computer Science Department at the University of Louisiana at Lafayette (UL Lafayette), USA

Date/Time: Thursday June 2, 2022 - 9:00 am

Keynote Tile: Smart Connected World: Is it Ready for Pandemic

Abstract: TBA

Dr. Bayoumi has been a faculty member in CACS since 1985. He received B.Sc. and M.Sc. degrees in Electrical Engineering from Cairo University, Egypt; M.Sc. degree in Computer Engineering from Washington University, St. Louis; and Ph.D. degree in Electrical Engineering from the University of Windsor, Canada. Dr. Bayoumi is the recipient of the 2009 IEEE Circuits and Systems Meritorious Service Award. Dr. Bayoumi is the recipient of the IEEE Circuits and Systems Society 2003 Education Award, and he is an IEEE Fellow. He was on the governor’s commission for developing a comprehensive energy policy for the State of Louisiana. He represented the CAS Society on the IEEE National Committee on Engineering R&D policy, IEEE National Committee on Communication and Information Policy, and IEEE National Committee on Energy Policy. He is also active in the “Renewable & Green Energy” and “Globalization: Technology, Economic and Culture” fields. He was a free lance columnist for Lafayette’s newspaper.

Dr. Bayoumi has graduated more than 44 Ph.D. and about 175 Master’s students. He has published over 300 papers in related journals and conferences. He edited, co-edited and co-authored 5 books in his research interests. He was and has been Guest Editor (or Co-Guest Editor) of eight special issues in VLSI Signal Processing, Learning on Silicon, Multimedia Architecture, Digital and Computational Video, Perception on a Chip, and Systems on a Chip. He has given numerous invited lectures and talks nationally and internationally, and has consulted in industry.

Dr. Bayoumi is the Vice President for Conferences of the IEEE Circuits and Systems (CAS) Society, where he has served in many editorial, administrative, and leadership capacities, including Vice President for Technical Activities. He was Chair and Founder of “Circuits and Systems for Communication” Technical Committee. He was Chair of VLSI Systems and Applications (VSA) Technical Committee (TC). He was General Chair of the Workshop on Computer Architecture for Machine Perception, 1993, New Orleans. He was General Chair of the IEEE International Midwest Symposium on Circuits and Systems (MWSCAS 1994) (Lafayette), and Co-General Chair of MWSCAS 2003 (Cairo). Dr. Bayoumi served as General Chair of the Great Lakes Symposium on VLSI (GLS 1998), Lafayette, LA; General Chair of the VLSI Signal Processing Systems Workshop (SiPS 2000), Lafayette, LA; General Chair of the International Workshop of Digital and Computational Video (DCV 2002), Clearwater Beach, FL; General Chair of the IEEE Computer Society Symposium on VLSI (ISVLSI 2004), Lafayette, LA, Chair of the IEEE International Midwest Symposium on Circuits and Systems (MWSCAS 2003); General Chair of the IEEE International Symposium on Circuits and Systems ( ISCAS 2007); and General Chair of the IEEE International Conference on Image Processing ( ICIP 2009).

He was Associate Editor of the Circuits and Devices Magazine, Transaction on VLSI Systems, Transaction on Neural Networks, and Transaction on Circuits and Systems II. Dr. Bayoumi is Associate Editor of INTEGRATION, VLSI Journal and Journal of VLSI Signal Processing Systems. He was Associate Editor of the Journal of Circuits, Systems, and Computers. He is Regional Editor for the VLSI Design Journal and on the Advisory Board of the Journal on Microelectronics Systems Integration. Dr. Bayoumi served on the Distinguished Visitors Program for IEEE Computer Society, 1991-1994, and Circuits and Systems Distinguished Program, 1999-2001. Dr. Bayoumi was Chair of the ASSP Technical Committee on Signal Processing Systems Design and Implementation. He is Faculty Advisor for the IEEE Computer Student Chapter at UL Lafayette, the winner of the 2002 Outstanding Chapter Award. He won UL Lafayette 1988 Researcher of the Year award and 1993 Distinguished Professor award at UL Lafayette.